Data Modeler Clinical R&D

We are seeking an experienced R&D Data Modeler to join clinical Data Management team. In this role, you ll play a critical part in designing and governing the data architecture that powers our R&D digital and analytics initiatives. You'll partner across business, digital, and IT teams to build scalable, reusable data models that support clinical, research, regulatory, and operational domains.

Key Responsibilities

Data Modeling & Architecture

• Design and maintain conceptual, logical, and physical data models aligned to R&D objectives.
• Develop standard data models and ontologies across R&D areas including Research, Clinical, and Regulatory.
• Partner with data product teams to create reusable and actionable data products.
• Optimize physical schemas for performance, minimizing latency for analytics and AI use.

Solution Design & Integration

• Serve as the subject matter expert for data integration across legacy and modern platforms.
• Define modeling standards, naming conventions, and harmonization rules.
• Collaborate with cross-functional teams to translate business needs into robust data solutions.

Governance & Best Practices

• Apply data governance frameworks to ensure regulatory compliance (GxP, FAIR principles).
• Establish best practices for version control, documentation, and model lifecycle management.
• Evaluate and recommend modern data modeling tools and platforms.

Consulting & Enablement

• Facilitate workshops to capture data requirements and define future-state architectures.
• Educate and advise R&D teams on modeling methodologies and metadata management.
• Support enterprise data initiatives as a lead data consultant.

Qualifications

• Bachelor s degree in Computer Science, Data Management, or a related health/science field.
• 12 years of work exp with the last 5+ years of experience in data modeling or information architecture within the pharmaceutical R&D domain.
• Proficiency in designing complex data models with strong business alignment.
• Deep understanding of R&D domains (Clinical Ops, Safety, Regulatory) and compliance (GxP).
• Strong experience in ETL/ELT pipelines, data integration, and metadata management.
• Familiarity with tools like Databricks, Informatica, ERwin, Reltio, and cloud platforms (Azure, AWS, Oracle).
• Knowledge of SDLC, change control, and validation processes.
• Excellent analytical, communication, and stakeholder engagement skills.
• Self-driven, collaborative, and passionate about data excellence.